For many utilities, trees are the number-one cause of all unplanned distribution outages. Most damage to electric utility systems during storms is caused by a falling tree or branch that takes power lines out of service. In order to help reduce the frequency of tree damage to utility systems, many utilities implement vegetation management programs as a preventative measure. North American utilities spend $7 billion to $10 billion annually on vegetation management in an effort to prevent service interruptions and safety hazards associated with trees contacting conductors.
Traditionally, vegetation management programs have relied on regular surveying and pruning by arborist teams to help control vegetation around utility systems, but the sheer number of utility lines covering vast distances makes it impractical, in many cases, to send survey teams on the ground. As a result, many utility companies have turned in the past to aerial reconnaissance techniques to provide photographic imagery of their utility systems which can be examined for possible vegetation growth issues. The material has included both nadir-looking or oblique imaging techniques, with still images and video. Unfortunately, such aerial image material does not provide the dimensional data necessary to judge whether or not a tree nearby a utility system is a risk for interfering with the utility if the tree were to fall over. From such data, determining accurate reach of the trees, and their ability to violate the safety zones of the conductors if they fall, is very limited. More recently, vegetation managers have turned to aerial reconnaissance systems which can provide three-dimensional data, such as LiDAR (light detection and ranging) systems to learn more about the vegetation adjacent to their power systems. For example, U.S. Pat. Nos. 6,792,684 and 7,474,964 disclose methods which analyze an overhead perspective of aerial LiDAR data to determine tree heights, a tree crown size, an assumed location for a tree based on the highest point in the tree crown, and a stem or trunk diameter. The tree height and crown-size information can be compared to known configurations in order to predict a tree's species, age, and development class. Techniques, such as those disclosed in U.S. Pat. No. 7,212,670, are even known to estimate stem size (trunk size) from a comparison of tree height with publicly obtainable forestry data. Unfortunately, none of the known LiDAR methods enable the determination of an accurate location for a tree's stem origin (also known as a seed point, stump point, or trunk location, where the tree grows out of the ground). As mentioned for the above patents, as well as in U.S. Pat. No. 7,539,605, trunk locations are currently estimated to be directly under the highest point in the tree crown. While this assumption may be generally valid for a tree growing on its own or for trees surrounded on all sides by a number of other trees in a forest, it often leads to incorrect stem origin location for trees growing on the edge of an opening in the canopy, for example a right of way (ROW), such as a power line corridor or railroad corridor.
Along ROW's the vegetation often has a tendency to grow towards the opening due to better availability of sunlight. This moves the crown centers, during the course of growth, outside the horizontal location of the tree stem origin, causing the trees and vegetation to “lean” towards the openings.
When existing remote sensing and other crown-recognizing methodologies are applied to locate the vegetation, crowns (typically, perimeters, centroid or tops) are often the targets sensed and located, lacking precise information about actual ownership—as defined by the stem origin position. The lack of precise location information can cause management challenges, since ownership, naturally, defines the right to decide on cutting, felling, thinning, side-trimming, or delimbing trees.
Often, tree crowns grow beyond ownership or management right boundaries. Especially often, this happens on right-of-ways (ROWs), which are legal entities, giving the management rights of the area inside ROW to the ROW-holders. ROWs are necessary for managing, for example, utility lines, distribution power lines, gas pipes, communication lines, roads, railroads, etc.
Aside from the need to understand the actual location of a tree crown versus the ROW boundaries, it is also important to know the actual stem origin in order to predict the proper path a tree could follow if knocked-over, broken, or cut down. The stem origin of the tree is often used as a pivot point in falling tree analysis, but the prior art's assumption that the stem origin is located beneath the highest point of a tree's crown can often lead to inaccurate results. The falling path of the tree may be defined as the set of points the tree may touch if it falls towards a certain direction. Falling path analysis is used, for example, to determine whether a tree, if it falls, may hit a power line conductor. The geometric analysis of falling vegetation is dependent on the geometry between the top of the vegetation, the location of the construction analyzed and the location of the bearing point used to rotate the falling tree around. Unfortunately, falling tree analysis is currently done using a horizontal projection of the point analyzed (such as the highest crown point) to the ground level as a bearing point. Resultant inaccurate bearing point locations result in improper falling vegetation analysis.
Therefore, it would be very desirable to have an economical, reliable, and easy to use method and system for locating a stem of a target tree.